Prospects of Using AI Technologies in Open Journal Systems (OJS)

Abstract

Open Journal Systems (OJS) is a widely used open-source platform for managing and publishing academic journals (Ndungu, 2020), (Hunter, 2010), (Tabatadze B. , 2024). Its modular design and open framework provide opportunities for integrating artificial intelligence (AI) technologies, which hold transformative potential for academic publishing. AI can enhance OJS by automating editorial workflows, improving user experience, and fostering global accessibility. Key areas for AI integration include automated peer review, where natural language processing (NLP) can identify relevant reviewers, detect plagiarism, and ensure structural compliance. AI-powered recommendation systems can personalize content delivery, offering tailored article suggestions based on user preferences and behaviors. Additionally, linguistic diversity can be bolstered through real-time translation tools and speech-to-text features, facilitating broader engagement with a global audience. AI also enables automation in editorial processes such as grammar checks, citation management, and abstract generation. Advanced analytics powered by AI can provide actionable insights into readership trends, engagement metrics, and impact factor predictions, supporting strategic decision-making for journal administrators. Despite its potential, AI integration poses challenges, including technical expertise requirements, financial constraints, and ethical concerns such as data privacy and bias. Overcoming these barriers will require careful planning and community collaboration. The future of AI in OJS looks promising, with opportunities to incorporate blockchain, adaptive learning systems, and AI-driven collaboration tools. By addressing these challenges, OJS can lead the evolution of open-access publishing, enhancing efficiency, accessibility, and inclusivity in scholarly communication.

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